Instructions to use abehandlerorg/econbertabstractclassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abehandlerorg/econbertabstractclassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abehandlerorg/econbertabstractclassifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abehandlerorg/econbertabstractclassifier") model = AutoModelForSequenceClassification.from_pretrained("abehandlerorg/econbertabstractclassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from abehandlerorg/econbertabstractclassifier: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/abehandlerorg/econbertabstractclassifier/resolve/main/model.safetensors
- Command line
-
hf download hf://abehandlerorg/econbertabstractclassifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/abehandlerorg/econbertabstractclassifier/resolve/main/model.safetensors
268 MB
- Xet hash:
- dc643de3691863472a5562fca3bd1aeed11d403d7ae27c6fb28868d8d63c5e2b
- Size of remote file:
- 268 MB
- SHA256:
- d3808ae7bf122b6fe95b131f06222c6fba13b39bd5c1b87cc158b502875a1475
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